Try our BETA version of Cell type Prediction now for free

Contact us
  • Species: human
  • Number of cells: 2147
  • Number of downloads: 8
  • Study size: 25MB
  • Uploaded at: Jun 18, 2022

Spatially discrete signalling niches regulate fibroblast heterogeneity in human lung cancer (Merged stromal cell)

CJ Hanley, S Waise, R Parker, MA Lopez, J Taylor, LM Kimbley, J West, CH Ottensmeier, MJJ Rose-Zerilli, GJ Thomas

Fibroblasts are functionally heterogeneous cells, capable of promoting and suppressing tumour progression. Across cancer types, the extent and cause of this phenotypic diversity remains unknown. We used single-cell RNA sequencing and multiplexed immunohistochemistry to examine fibroblast heterogeneity in human lung and non-small cell lung cancer (NSCLC) samples. This identified seven fibroblast subpopulations: including inflammatory fibroblasts and myofibroblasts (representing terminal differentiation states), quiescent fibroblasts, proto-myofibroblasts (x2) and proto-inflammatory fibroblasts (x2). Fibroblast subpopulations were variably distributed throughout tissues but accumulated at discrete niches associated with differentiation status. Bioinformatics analyses suggested TGF-β1 and IL-1 as key regulators of myofibroblastic and inflammatory differentiation respectively. However, in vitro analyses showed that whilst TGF-β1 stimulation in combination with increased tissue tension could induce myofibroblast marker expression, it failed to fully re-capitulate ex-vivo phenotypes. Similarly, IL-1β treatment only induced upregulation of a subset of inflammatory fibroblast marker genes. In silico modelling of ligand-receptor signalling identified additional pathways and cell interactions likely to be involved in fibroblast activation, which can be examined using publicly available R shiny applications (at the following links: myofibroblast activation and inflammatory fibroblast activation). This highlighted a potential role for IL-11 and IL-6 (among other ligands) in myofibroblast and inflammatory fibroblast activation respectively. This analysis provides valuable insight into fibroblast subtypes and differentiation mechanisms in NSCLC.

Back to datasets